Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It usefully discloses concurrency, parallelism, and sub-second performance, but it does not mention failure behavior, partial results, rate limits, or what the enrichment returns. Some transparency is present, but not full.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The core capability and limit are front-loaded, and the use-case sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter batch tool, the description covers the action, limit, concurrency, and intended use case. It is slightly incomplete because it does not describe the output or explicitly route single-domain requests to enrich_company, but the schema covers invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the only parameter, 'domains', is already described as an array of up to 50 apex domains. The description adds the 'company' qualifier and concurrency context, but does not materially extend parameter semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Enriches'), a precise resource ('company domains'), and a clear scope ('up to 50', 'concurrently in parallel'). The 'batch' prefix and domain scope distinguish it from siblings like enrich_company and detect_technology without needing to open the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear usage context: 'Highly efficient for lead qualification waterfalls.' It does not explicitly name alternatives or state when not to use it, but the batch-vs-single distinction from enrich_company is strongly implied by 'up to 50' and 'batch'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of disclosing behavior. The description states it 'checks' but does not reveal what the tool returns (e.g., a boolean, evidence, or details), whether it performs any side effects, or if it has network/rate limits. It also does not explicitly state that it is a read-only operation. For a tool that likely performs a network lookup, this lack of behavioral context leaves the agent uncertain about expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the action and provides a clear list of example technologies. There is no filler or redundant information. It is appropriately concise for a simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity, the description covers the basic purpose, but it omits critical details: there is no output schema, so the return format is unspecified, and the description does not mention how results are presented (e.g., boolean, confidence score, or details). Additionally, there is no mention of potential failure modes (e.g., unknown domain or technology) or whether the tool requires authentication. The lack of usage guidance for sibling distinction also reduces completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes both parameters with examples and the description only reiterates those examples (e.g., 'stripe', 'ashby') without adding new meaning. The schema coverage is 100%, so the baseline is 3. The description does not clarify any parameter-specific constraints beyond what the schema states, such as how the technology signature is matched or any format requirements.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Checks') and clearly identifies the resource ('a specific target technology') and scope ('used by a company domain'). Examples of technologies are given, and the tool is distinct from the sibling enrichment tools, which focus on adding data about companies rather than detecting specific technology usage. No ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide any guidance on when to use this tool versus siblings like batch_enrich_companies or enrich_company. It does not mention scenarios where this tool is preferred, nor does it state exclusions or alternatives. While the purpose is clear, the agent is left to infer when this tool should be chosen over enrichment tools, which serve a different function but are grouped as siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the burden, and it does add useful behavioral context: ~240 token output, 140ms latency, 'verified' data, and specific returned signals. It does not disclose failure modes, data freshness, auth needs, or what happens for unsupported domains, so coverage is partial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One dense sentence front-loads the core purpose and then lists high-value specifics such as token count, latency, and output categories. There is no filler or duplication of schema content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description summarizes output categories well and gives a clear input signal, but it omits error behavior, usage boundaries against siblings, and any caveats about data verification or availability. Given the lack of an output schema and annotations, a bit more context would be needed for full confidence.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the domain parameter already has a clear description with examples. The tool description adds little beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Fetches') and resource ('verified, token-minified B2B company firmographics'), and it itemizes the returned data categories, so an agent can tell what the tool does. It does not explicitly contrast itself with siblings like detect_technology or batch_enrich_companies, so it stops short of full sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The use case is implied: call this when you need firmographic enrichment for a single company domain. However, there is no explicit when-to-use guidance, no mention of when not to use it, and no routing to batch_enrich_companies for multiple domains.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.